Eine Plattform für die Wissenschaft: Bauingenieurwesen, Architektur und Urbanistik
Eine Plattform für die Wissenschaft: Bauingenieurwesen, Architektur und Urbanistik
Multiple linear regression and genetic algorithm approaches to predict temporal scour depth near circular pier in non-cohesive sediment
Pier scour is a major problem for the safe and economical design of bridges. Large number of field and laboratory studies have been conducted to investigative the effect of significant variables. Present study is an attempt to develop a generalized scour prediction equation to investigate temporal variation of scour around circular bridges utilizing the data generated from our experimental study as well as data collected by earlier researchers. Nearly 1100 laboratory experimental data-sets were compiled and utilized to develop the generalized scour equation using MLR and GA. The scour depth predicted using GA was found to be more accurate than MLR. Further, the equation developed in the present study was compared to the previously proposed equations. It was found that the present equation complies with observed data better than the previously proposed equations. About 20% and 35% data-sets are found to be within the ±25% error line using previously proposed equations, while GA-based relationship gave about 52% of the data points within ±25% error line.
Multiple linear regression and genetic algorithm approaches to predict temporal scour depth near circular pier in non-cohesive sediment
Pier scour is a major problem for the safe and economical design of bridges. Large number of field and laboratory studies have been conducted to investigative the effect of significant variables. Present study is an attempt to develop a generalized scour prediction equation to investigate temporal variation of scour around circular bridges utilizing the data generated from our experimental study as well as data collected by earlier researchers. Nearly 1100 laboratory experimental data-sets were compiled and utilized to develop the generalized scour equation using MLR and GA. The scour depth predicted using GA was found to be more accurate than MLR. Further, the equation developed in the present study was compared to the previously proposed equations. It was found that the present equation complies with observed data better than the previously proposed equations. About 20% and 35% data-sets are found to be within the ±25% error line using previously proposed equations, while GA-based relationship gave about 52% of the data points within ±25% error line.
Multiple linear regression and genetic algorithm approaches to predict temporal scour depth near circular pier in non-cohesive sediment
Pandey, Manish (Autor:in) / Zakwan, Mohammad (Autor:in) / Sharma, P. K. (Autor:in) / Ahmad, Z. (Autor:in)
ISH Journal of Hydraulic Engineering ; 26 ; 96-103
02.01.2020
8 pages
Aufsatz (Zeitschrift)
Elektronische Ressource
Englisch
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